Dynamic resource distribution using periodicity-aware predictive modeling

A non-transitory computer readable medium having stored thereon a sequence of instructions which, when executed by a processor performs a set of acts comprising:

• maintaining, at a storage pool, measurements corresponding to prior usage of a distributed storage resource of a cluster by a plurality of nodes in the cluster, the storage pool comprising an aggregation of one or more storage devices directly attached to respective nodes in the cluster;
• receiving, at a first node of the plurality of nodes in the cluster, the measurements from the storage pool;
• determining, at the first node, a time period for a training window corresponding to a portion of the measurements, wherein the training window bounds a periodically recurring portion of the measurements;
• training, at the first node, a predictive model based at least in part on the periodically recurring portion of the measurements to produce a trained predictive model;
• and
• determining a resource allocation operation based at least in part on a prediction from the trained predictive model.

A system, comprising:

• a storage medium having stored thereon a sequence of instructions;
• and
• a processor that executes the sequence of instructions to perform a set of acts comprising:
• maintaining, at a storage pool, measurements corresponding to prior usage of a distributed storage resource of a cluster by a plurality of nodes in the cluster, the storage pool comprising an aggregation of one or more storage devices directly attached to respective nodes in the cluster;
• receiving, at a first node of the plurality of nodes in the cluster, the measurements from the storage pool;
• determining, at the first node, a time period for a training window corresponding to a portion of the measurements, wherein the training window bounds a periodically recurring portion of the measurements;
• training, at the first node, a predictive model based at least in part on the periodically recurring portion of the measurements to produce a trained predictive model;
• and
• determining a resource allocation operation based at least in part on a prediction from the trained predictive model.